Exploring bearing root mean square first passage time based on inverse Gaussian distribution

Sutawanir Darwis (), Nusar Hajarisman (), Suliadi Suliadi () and Achmad Widodo ()
Additional contact information
Sutawanir Darwis: Bandung Islamic University
Nusar Hajarisman: Bandung Islamic University
Suliadi Suliadi: Bandung Islamic University
Achmad Widodo: Diponegoro University

No 12613369, Proceedings of Business and Management Conferences from International Institute of Social and Economic Sciences

Abstract: Bearing becomes a critical rotational component in mechanical system, and its condition will affect the system. It is essential to predict bearing lifetime through acquisition and process degradation prediction. Vibration data contain information bearing degradation, and analysis based on this information is frequently applied in bearing prognostic. Proper models should be developed in order to find the relationship between degradation process and covariates. First passage time is a critical parameter in Brownian motion representing the time point when degradation curve passes through the failure for the first time, which equals to lifetime of the bearing. It is a random process that follows the inverse Gaussian distribution. This paper explores the application of first passage time of bearing vibration using bearing lifetime and operating condition as covariate. The lifetime data is extracted from bearing vibration data PHM Pronostia FEMTO database. The research methodology consist of inverse Gaussian parameter estimation, and interpretation of reliability of first passage analysis of operating condition.

Keywords: bearing lifetime; estimation inverse Gaussian; bearing operating condition; reliability first passage time (search for similar items in EconPapers)
JEL-codes: C00 C80 (search for similar items in EconPapers)
Pages: 8 pages
Date: 2021-10
New Economics Papers: this item is included in nep-ore
References: Add references at CitEc
Citations:

Published in Proceedings of the Proceedings of the 12th Business & Management Conference, Prague, Oct 2021, pages 9-16

Downloads: (external link)
https://iises.net/proceedings/12th-business-manage ... 27&iid=002&rid=13369 First version, 2021

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sek:ibmpro:12613369

Access Statistics for this paper

More papers in Proceedings of Business and Management Conferences from International Institute of Social and Economic Sciences
Bibliographic data for series maintained by Klara Cermakova ().